On Tue, Jan 31, 2012 at 10:28:55AM -0800, Michael Waskom wrote: > First, I realized that my original PCA did not make much sense. What > I want to do is reduce the feature dimensions in my classification, > but keep the number of observations.
That's what the scikit's PCA does. I don't understand why you need to transpose the data. > One important question, though, is whether it will be valid to scale > my features within each run. My intuition is that it's fine as long > as I am doing leave-one-run-out cross validation, as the test set > won't have been transformed with any parameters determined from the > training set. I agree with you. It seems to me a reasonnable solution. Gael ------------------------------------------------------------------------------ Keep Your Developer Skills Current with LearnDevNow! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-d2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
